Going with Anthropic or OpenAI, despite on the surface having that clean Apple smell and feel, carries a lot of risk Apple's part. Both companies are far underwater, liable to take risks, and liable to drown if they even fall a bit behind.
Definitely. At at this point, Apple just needs to get anything out the door. It was nearly two years ago they sold a phone with features that still haven't shipped and the promise that Apple Intelligence would come in two months.
It’s just how Apple does things: They still have no folding phone, under-screen finger print scanner, under-screen front-cam, etc.
To the extent Cupertino fucked up, it's in having had this attitude when they rolled out Apple Intelligence.
There isn't currently a forcing function. Apple owns the iPhone, and that makes it an emperor among kings. Its wealth is also built on starting with user problems and then working backwards to the technology, versus embracing whatever's hot and trying to shove it down our throats.
They don't though, Android is clearly ahead in AI integration (even Samsung are running TV ads mocking iPhones AI capability) yet still iPhones sales are breaking records - the majority of their phone buyers still prefer an iPhone over an AI capable other phone.
They can take their time to develop AI integration that others can't deploy - 'secure/private', deep integration with iCloud, location services, processing on device etc. that will provide the product moat to increase sales.
Will make it much easier to find those missing pictures from a few years ago...
Just under 16 months since the release of iOS 18. The phones they would have sold this with shipped alongside 18.
Also, the personalized Siri was indicated it would not be available until later and was expected in the spring release (March 2025).
Anthropic doesn't have a single data centre, they rent from AWS/Microsoft/Google.
I respect Google's engineering, and I'm aware that fundamental technologies such as Protocol Buffers and FlatBuffers are unavoidably integrated into the software fabric, but this is is avoidable.
I'm surprised Google aren't paying Apple for this.
Personally I wouldn't use it, it still belongs to an advertiser specialised on extracting user information. Not that I expect that other AI companies value privacy much higher. But clean smell also means bland smell.
I don't however like the idea of having Google deeply embedded in my machine and Siri will definitely be turned off when this happens. I only use Siri as an egg timer anyway.
This seems like a odd move for a company that sells privacy.
Given my stance about AI, I'll definitely not use it, but I understand Apple's choice. Also this choice will give them enough time to develop their infrastructure and replace parts of it with their own, if they are planning to do it.
> Not that I expect that other AI companies value privacy much higher.
Breaching privacy and using it for its own benefit is AIs business model. There are no ethical players here. Neither from training nor from respecting their users' privacy perspective. Just next iteration of what social media companies do.
I dont think the model is that much different if they thought Siri was half decent enough for so long.
Judging from the past 10 years, I would say this is more likely driven by part of a bigger package deal with Google Search Placement and Google Cloud Services. When everything else being roughly equal.
Instead of raising price again Paying Apple even more per user, How about we pay the less but throw in Gemini with it?
Apple has been very good, if not the best at picking one side and allowing the others to fight for its contract. They dont want Microsoft to win the AI race, at the same time Apple is increasing the use of Azure just in case. Basically playing the game of leverage at its best. In hindsight probably too well into it they forgot what the real purpose of all these leverage are for, not cost savings but ultimately better quality product.
Can the DOJ and FTC look into this?
Google shouldn't be able to charge a fee on accessing every registered trademark in the world. They use Apple get get the last 30% of "URL Bars", I mean Google Search middlemen.
Searching Anthropic gets me a bidding war, which I'm sure is bleeding Google's competition dry.
We need a "no bare trademark (plus edit distance) ads or auto suggest" law. It's made Google an unkillable OP monster. Any search monopoly or marketplace monopoly should be subject to not allowing ads to be sold against a registered trademark database.
Apple has the best edge inference silicon in the world (neural engine), but they have effectively zero presence in a training datacenter. They simply do not have the TPU pods or the H100 clusters to train a frontier model like Gemini 2.5 or 3.0 from scratch without burning 10 years of cash flow.
To me, this deal is about the bill of materials for intelligence. Apple admitted that the cost of training SOTA models is a capex heavy-lift they don't want to own. Seems like they are pivoting to becoming the premium "last mile" delivery network for someone else's intelligence. Am I missing the elephant in the room?
It's a smart move. Let Google burn the gigawatts training the trillion parameter model. Apple will just optimize the quantization and run the distilled version on the private cloud compute nodes. I'm oversimplifying but this effectively turns the iPhone into a dumb terminal for Google's brain, wrapped in Apple's privacy theater.
Setting aside the obligatory HN dig at the end, LLMs are now commodities and the least important component of the intelligence system Apple is building. The hidden-in-plain-sight thing Apple is doing is exposing all app data as context and all app capabilities as skills. (See App Intents, Core Spotlight, Siri Shortcuts, etc.)
Anyone with an understanding of Apple's rabid aversion to being bound by a single supplier understands that they've tested this integration with all foundation models, that they can swap Google out for another vendor at any time, and that they have a long-term plan to eliminate this dependency as well.
> Apple admitted that the cost of training SOTA models is a capex heavy-lift they don't want to own.
I'd be interested in a citation for this (Apple introduced two multilingual, multimodal foundation language models in 2025), but in any case anything you hear from Apple publicly is what they want you to think for the next few quarters, vs. an indicator of what their actual 5-, 10-, and 20-year plans are.
Google and Apple together will posttrain Gemini to Apple's specification. Google has the know-how as well as infra and will happily do this (for free ish) to continue the mutually beneficial relationship - as well as lock out competitors that asked for more money (Anthropic)
Once this goes live, provided Siri improves meaningfully, it is quite an expensive experiment to then switch to a different provider.
For any single user, the switching costs to a different LLM are next to nothing. But at Apple's scale they need to be extremely careful and confident that the switch is an actual improvement
Seems like they are waiting for the "slope of enlightenment" on the gartner hype curve to flatten out. Given you can just lease or buy a SOTA model from leading vendors there's no advantage to training your own right now. My guess is that the LLM/AI landscape will look entirely different by 2030 and any 5 year plan won't be in the same zip code, let alone playing field. Leasing an LLM from Google with a support contract seems like a pretty smart short term play as things continue to evolve over the next 2-3 years.
Apple won't switch Google out as a provider for the same reason Google is your default search provider. They don't give a shit about how many advertisements you're shown. You are actually detached from 2026 software trends if you think Apple is going to give users significant backend choices. They're perfectly fine selling your attention to the highest bidder.
LLMs are now commodities and the least important component of the intelligence system Apple is building
My money is still on Apple and Google to be the winners from LLMs.
So I'm glad Apple is not trying to get too much into a bidding war. As for how well orgs are run, Meta has its issues as well (cf the fiasco with its eponymous product), while Google steadily seems to erode its core products.
The Allen Institute (a non-profit) just released the Molmo 2 and Olmo 3 models. They trained these from scratch using public datasets, and they are performance-competitive with Gemini in several benchmarks [0] [1].
AMD was also able to successfully train an older version of OLMo on their hardware using the published code, data, and recipe [2].
If a non-profit and a chip vendor (training for marketing purposes) can do this, it clearly doesn't require "burning 10 years of cash flow" or a Google-scale TPU farm.
[0]: https://allenai.org/blog/molmo2
I'm curious if this officially turns the foundation model providers into the new "dumb pipes" of the tech stack?
This sort of thing didn't work out great for Mozilla. Apple, thankfully, has other business bringing in the revenue, but it's still a bit wild to put a core bit of the product in the hands of the only other major competitor in the smartphone OS space!
Down the road Apple has an advantage here in a super large training data set that includes messages, mail, photos, calendar, health, app usage, location, purchases, voice, biometrics, and you behaviour over YEARS.
Let's check back in 5 years and see if Apple is still using Gemini or if Apple distills, trains and specializes until they have completed building a model-agnostic intelligence substrate.
It goes back much further than that - up until 2016, Apple wouldn't let its ML researchers add author names to published research papers. You can't attract world-class talent in research with a culture built around paranoid secrecy.
Would giving more money/shares help?
The moat is talent, culture, and compute. Apple doesn't have any of these 3 for SOTA AI.
It sounds like the value of these very time-consuming, resource-intensive, and large scale operations is entirely self-contained in the weights produced at the end, right?
Given that we have a lot of other players enabling this in other ways, like Open Sourcing weights (West vs East AI race), and even leaks, this play by Apple sounds really smart and the only opportunity window they are giving away here is "first to market" right?
Is it safe to assume that eventually the weights will be out in the open for everyone?
A lot of the hype in LLM economics is driven by speculation that eventually training these LLMs is going to lead to AGI and the first to get there will reap huge benefits.
So if you believe that, being "first to market" is a pretty big deal.
But in the real world there's no reason to believe LLMs lead to AGI, and given the fairly lock-step nature of the competition, there's also not really a reason to believe that even if LLMs did somehow lead to AGI that the same result wouldn't be achieved by everyone currently building "State of the Art" models at roughly the same time (like within days/months of each other).
So... yeah, what Apple is doing is actually pretty smart, and I'm not particularly an Apple fan.
Yes, and the knowledge gained along the way. For example, the new TPUv4 that Google uses requires rack and DC aware technologies (like optical switching fabric) for them to even work at all. The weights are important, and there is open weights, but only Google and the like are getting the experience and SOTA tech needed to operate cheaply at scale.
So what does it take? How many actual commitments to privacy does Apple have to make before the HN crowd stops crowing about "theater"?
(And even if you do believe it, they also aren't licensing the IP they're training on, unlike american firms who are now paying quite a lot for it)
https://machinelearning.apple.com/research/apple-intelligenc...
They have always been a premium "last mile" delivery network for someone else's intelligence, except that "intelligence" was always IP until now. They have always polished existing (i.e., not theirs) ideas and made them bulletproof and accessible to the masses. Seems like they intend to just do more of the same for AI "intelligence". And good for them, as it is their specialty and it works.
Mullvad requires nothing but an envelope with cash in it and a hash code and stores nothing. Apple owns you.
They also were deceptive about iCloud encryption where they claimed that nobody but you can read your iCloud data. But then it came out after all their fanfare that if you do iCloud backups Apple CAN read your data. But they aren’t in a hurry to retract the lie they promoted.
Also if someone in another country messages you, if that country’s laws require that Apple provide the name, email, phone number, and content of the local users, guess what. Since they messaged you, now not only their name and information, but also your name and private information and message content is shared with that country’s government as well. By Apple. Do they tell you? No. Even if your own country respects privacy. Does Apple have a help article explaining this? No.
It also lets Apple stand by while the dust settles on who will out innovate in the AI war - they could easily enter the game on a big way much later on.
I can see a future where LLM research stalls and stagnates, at which point the ROI on building/maintaining their own commodity LLM might become tolerable. Apple has had Siri as a product/feature and they've proven for the better part of a decade that voice assistants are not something they're willing to build a proficiency in. My wife still has an apple iPhone for at least a decade now, and I've heard her use Siri perhaps twice in that time.
Google really could care less about Android being good. It is a client for Google search and Google services - just like the iPhone is a client for Google search and apps.
AAPL has approximately $35 billion of cash equivalents on hand. What other use may they have for this trove? Buy back more stocks?
Why does Apple need to build its own training cluster to train a frontier model, anyway?
Why couldn't the deal we're reading about have been "Apple pays Google $200bn to lease exclusive-use timeslots on Google's AI training cluster"?
> without burning 10 years of cash flow.
They are only ones who do not have large debts off(or on) balance sheet or aggressive long term contracts with model providers and their product demand /cash flow is least dependent on the AI industry performance.
They will still be affected by general economic downturn but not be impacted as deeply as AI charged companies in big tech.
I feel like people probably said this when Google became the default search engine for everyone...
Can you cite this claim? The Qualcomm Hexagon NPU seems to be superior in the benchmarks I've seen.
Everyone using Siri is going to have their personality data emulated and simulated as a ”digital twin” in some computing hell-hole.
Don't they have the highest market cap of any company in existence?
apple to some users "are you leaving for android because of their ai assistant? don’t leave we are bringing it to iphone"
Probably not missing the elephant. They certainly have the money to invest and they do like vertical integration but putting massive investment in bubble that can pop or flatline at any point seems pointless if they can just pay to use current best and in future they can just switch to something cheaper or buy some of the smaller AI companies that survive the purge.
Given how much AI capable their hardware is they might just move most of it locally too
There is no intelligence
Wasn't Apple sitting on a pile of cash and having no good ideas what to spend it on?
Edit: especially given that Apple doesn’t do b2b so all the spend would be just to make consumer products
They still generate about ~$100 billion in free cash per year, that is plowed into the buybacks.
They could spend more cash than every other industry competitor. It's ludicrous to say that they would have to burn 10 years of cash flow on trivial (relative) investment in model development and training. That statement reflects a poor understanding of Apple's cash flow.
Apple is flush with cash and other assets, they have always been. They most likely plan to ride out the AI boom with Google's models and buy up scraps for pennies on the dollar once the bubble pops and a bunch of the startups go bust.
It wouldn't be the first time they went for full vertical integration.
https://daringfireball.net/linked/2026/01/12/apple-google-fo...
"Apple Intelligence will continue to run on Apple devices and Private Cloud Compute, while maintaining Apple's industry-leading privacy standards."
Beyond Siri, Apple Foundation Models are available as API; will Google's technologies thus also be available as API? Will Apple reduce its own investment in building out the Foundation models?
"These models will help power future Apple Intelligence features, including a more personalized Siri coming this year."
1. The first issue is that there is significant momentum in calling Siri bad, so even if Apple released a higher quality version it will still be labelled bad. It can enhance the user's life and make their device easier to use, but the overall press will be cherrypicked examples where it did something silly.
2. Basing Siri on Google's Gemini can help to alleviate some of that bad press, since a non-zero share of that doomer commentary comes from brand-loyalists and astroturfing.
3. The final issue is that on-device Siri will never perform like server-based ChatGPT. So in a way it's already going to disappoint some users who don't realise that running something on mobile device hardware is going to have compromises which aren't present on a server farm. To help illustrate that point: We even have the likes of John Gruber making stony-faced comparisons between Apple's on-device image generator toy (one that produces about an image per second) versus OpenAI's server farm-based image generator which makes a single image in about 1-2 minutes. So if a long-running tech blogger can't find charity in those technical limitations, I don't expect users to.
> The final issue is that on-device Siri will never perform like server-based ChatGPT. So in a way it's already going to disappoint some users who don't realise that running something on mobile device hardware is going to have compromises which aren't present on a server farm.
For many years, siri requests were sent to an external server. It still sucked.
There are many times I want to type the same word that is already on the app screen but it autocorrects me to something completely different.
They have the time and the money and the customers, so I'm confident they will accomplish great things.
Even "Play the album XY" leads to Siri only playing the single song. It's hilariously bad.
Apple plainly doesn't believe in the uplift and impending AGI doom. Nor do they believe there's no value in AI services. They just think for NOW at least they can buy in better than they can own.
But based on Apples VLSI longterm vision, on their other behaviours in times past with IPR in any space, they will ultimately take ownership.
How? People have been saying this since CoreML dropped nine years ago. Apple is no closer to revamping Siri or rebuking CUDA than they were back then.
The non-hardware AI industry is currently in an R&D race to establish and maintain marketshare, but with Apple's existing iPhone, iPad and Mac ecosystem they already have a market share they control so they can wait until the AI market stabilizes before investing heavily in their own solutions.
For now, Apple can partner with solid AI providers to provide AI services and benefits to their customers in the short term and then later on they can acquire established AI companies to jumpstart their own AI platform once AI technology reaches more long term consistency and standardization.
Sounds like Apple Foundation Models aren't exactly foundational.
Maybe someday they'll build their own, the way they eventually replaced Google Maps with Apple Maps. But I think they recognize that that will be years away.
For who? Regular people are quite famously not clamouring for more AI features in software. A Siri that is not so stupendously dumb would be nice, but I doubt it would even be a consideration for the vast majority of people choosing a phone.
On the one hand, they apparently want to be a service provider Microsoft-style. They are just signing a partnership with their biggest competitor and giving them access to their main competitive advantage, the most advanced AI available.
On the other hand, they want to be another Apple. They are locking down their phone. Are competing with the manufacturers of the best Android phones. Are limiting the possibility of distributing software on their system. Things that were their main differentiator.
It doesn't make sense. It's also a giant middle finger to the people who bought the Pixel for Gemini. Congrats, you were beta testers for iPhone users who won't have to share their data with Google for training Gemini. I have rarely seen a company as disrespectful to its customer.
The idiomatic "British" way of doing this ...
Alternatively, for an Imperial-style approach, ...
As a professional software engineer you really should ...
(Because I just have a short blurb about my educational background, career, and geography in there, which with every other model I've tried works great to ensure British spelling, UK information, metric units, and cut the cruft because I know how to mkdir etc.)
It's given me a good laugh a few times, but just about getting old now.
Because Apple Silicon is so good for LLM inferencing, I hope they also do a deal for small on-device Gemma models.
The better the basic NLP tasks like named entity recognition, PoS tagging, Dependency Parsing, Semantic Role Labelling, Event Extraction, Constituency parsing, Classification/Categorization, Question Answering, etc, are implemented by the model layer, the farther you can go on implementing meaningful use-cases in your agent.
Apple can now concentrate on making Siri a really useful and powerful agent.
The biggest thing Apple has to do is get a generic pipeline up and running, that can support both cloud and non-cloud models down the road, and integrate with a bunch of local tools for agent-style workloads (e.g. "restart", "audio volume", "take screenshot" as tools that agents via different cloud/local models can call on-device).
But I saw something else in that statement. Is there going to be some quantized version of Gemini tailored to run on-device on an M4? If so, that would catapult Apple into an entirely new category merging consumer hardware with frontier models.
Was this just a massive oversight at Apple? Were there not AI researchers at Apple sounding the alarm that they were way off with their technology and its capabilities? Wouldn't there be talk within the industry that this form of AI assistant would soon be looked at as useless?
Am I missing something?
Siri was never an “AI agent”, with intent based systems, you give the system phrases to match on (intents) and to fulfill an intent, all of the “slots” have to be fulfilled. For instance “I want to go from $source to $destination” and then the system calls an API.
There is no AI understanding - it’s a “1000 monkeys implementation”, you just start giving the system a bunch of variations and templates you want to match on in every single language you care about and match the intents to an API. That’s how Google and Alexa also worked pre LLM. They just had more monkeys dedicated to creating matching sentences.
Post LLM, you tell the LLM what the underlying system is capable of, the parameters the API requires to fulfill an action and the LLM can figure out the users intentions and ask follow up questions until it had enough info to call the API. You can specify the prompt in English and it works in all of the languages that the LLM has been trained on.
Yes I’ve done both approaches
> Apple and Google have entered into a multi-year collaboration under which the next generation of Apple Foundation Models will be based on Google's Gemini models and cloud technology. These models will help power future Apple Intelligence features, including a more personalized Siri coming this year.
... https://blog.google/company-news/inside-google/company-annou...
That will be their contract writing AI.
I'm really curious how Apple is bridging the gap between consumer silicon and the datacenter scale stack they must have to run a customized Gemini model for millions of users.
RDMA over Thunderbolt is cool for small lab clusters but they must be using something else in the datacenter, right?
Last I heard most of their e2e storage for iCloud was on GCP.
They also use AWS.
I understand other things like image recognition, wikipedia information, etc require external data sets, and transferring over local data to that end can be a privacy breach. But the local stuff should be easy, at least in one or two languages.
In the original announcement of the Siri revamped a couple of years ago, they specifically talked about having the on-device model handle everything it can, and only using the cloud models for the harder or more open ended questions.
Might sound crazy but remember they did exactly this for web search. And Maps as well for many years.
This way they go from having to build and maintain Siri (which has negative brand value at this point) and pay Google's huge inference bills to actually charging Google for the privilege.
Apple weighs using Anthropic or OpenAI to power Siri
Amazon/AWS was trying to push its partnership with Apple hard once that was revealed, including vague references to doing AI things, but AWS is just way to far behind at this point so looks like they lost out here to Google/GCP.
Any details on privacy and data sharing surfaced yet?
https://blog.google/company-news/inside-google/company-annou...
I didn't realize that Apple could possibly be more stupid in their strategy with AI, but now they've given the game to their biggest competitor in every arena in which they compete.
It's truly amazing how badly they've flubbed it.
In September, a judge ruled against a worst-case scenario outcome that could have forced Google to divest its Chrome browser business.
The decision also allowed Google to continue to make deals such as the one with Apple."
How much is Google paying Apple now
If these anti-competitive agreements^1 were public,^2 headlines could be something like,
(A) "Apple agrees to use Google's Gemini for AI-powered Siri for $[payment amount]"
Instead, headlines are something like,
(B) "Apple picks Google's Gemini to run Ai-powered Siri"
1. In other words, they are exclusive and have anticompetitive effects
2. Neither CNBC nor I are suggesting that there is any requirement for the parties to make these agreements public. I am presenting a hypothetical relating to headlilnes, (A) versus (B), as indicated by the words "If" and "could"
Google pays 20 billion to Apple annually for search traffic
Apple allegedly pays Google about 1 billion per year for Gemini
Perhaps Gemini sends more search traffic to Google
The search traffic and data collection is worth far more than Gemini
https://www.bloomberg.com/news/articles/2025-12-01/openai-ta...
To be clear, I'd much rather have my personal cloud data private than have good AI integration on my devices. But strictly from an AI-centric perspective, Apple painted themselves into a corner.
Their image classification happens on-device, in comparison Google Photos does that server side so they already have ML infra.
"liquid ass" is how most of my friends describe it
Why does a MacBook seem better than PC laptops? Because Apple makes so few designs. When you make so few things, you can spend more time refining the design. When you're churning out a dozen designs a year, can you optimize the fan as well for each one? You hit a certain point where you say "eh, good enough." Apple's aluminum unibody MacBook Pro was largely the same design 2008-2021. They certainly iterated on it, but it wasn't "look at my flashy new case" every year. PC laptop makers come out with new designs with new materials so frequently.
With iPhones, Apple often keeps a design for 3 years. It looks like Samsung has churned out over 25 phone models over the past year while Apple has 5 (iPhone, iPhone Plus, iPhone Pro, iPhone Pro Max, iPhone 16e).
It's easy to look so good at things when you do fewer things. I think this is one of Apple's great strengths - knowing where to concentrate its effort.
They aren't.
I can't wait for gemini to lecture me why I should throw away my android
Oh, well. What could have been great.
By the way, have any of you ever tried to delete and disabled Siri’s iCloud backup? You can’t do it.
On iPhone, Settings → iCloud → Storage → Siri → Disable and Delete
Edit: Tried it. It works for me. Takes a minute though.
I don't expect the current US government to do anything about it though.
I admit I don't see the issue here. Companies are free to select their service providers, and free to dominate a market (as long as they don't abuse such dominant position).
https://support.apple.com/guide/iphone/use-chatgpt-with-appl...
So I'm guessing in a future update it will be Gemini instead. I hope it's going to be more of an option to choose between the 2.
But why on earth would they do that? It's both cheaper and safer to buy Google's model, with whom they already have a longstanding relationship. Examples include the search engine deal, and using Google Cloud infrastructure for iCloud and other services. Their new "private cloud compute" already runs on GCP too, perfect! Buying Gemini just makes sense, for now. Wait a few years until the technology becomes more mature/stable and then replace it with their own for a reasonable price.
It would take US antitrust approval, but under Trump, that's for sale.